Publicado por LAP LAMBERT Academic Publishing Nov 2016, 2016
ISBN 10: 365997921X ISBN 13: 9783659979217
Idioma: Inglés
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -Newer intrusions are coming out every day with the all-way growth of the Internet. In this context, this book proposes a hybrid approach of intrusion detection along with architecture. The proposed architecture is flexible enough to carry intrusion detection tasks either by using a single module or by using multiple modules. Two modules - (1) Clustering-Outlier detection followed by SVM classification and (2) Incremental SVM with Half-partition method, are proposed in the book. Firstly, this work develops the ¿Clustering-Outlier Detection' algorithm that combines k-Medoids clustering and Outlier analysis. Secondly, this book introduces the Half-partition strategy and also designs ¿Candidate Support Vector Selection¿ algorithm for incremental SVM. This book is intended for the people who are working in the field of Intrusion Detection and Data Mining. Researchers and Scholars who are interested in k-Means and k-Medoids clustering and SVM classification in particular, will find this book useful. Students who want to pursue their research work in the fields of Information Security and Data Mining may also consider this as a good reference.Books on Demand GmbH, Überseering 33, 22297 Hamburg 140 pp. Englisch.
Publicado por LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365997921X ISBN 13: 9783659979217
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoPaperback. Condición: Brand New. 140 pages. 8.66x5.91x0.32 inches. In Stock.
Publicado por LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365997921X ISBN 13: 9783659979217
Idioma: Inglés
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Añadir al carritoHardback. Condición: New. New copy - Usually dispatched within 4 working days. 174.
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Añadir al carritoHardcover. Condición: Brand New. 260 pages. 9.69x6.88x0.69 inches. In Stock.
Publicado por LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365997921X ISBN 13: 9783659979217
Idioma: Inglés
Librería: moluna, Greven, Alemania
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Chitrakar RoshanRoshan Chitrakar, born in 1967, is a Ph.D. in Information Security of Wuhan University, China. His areas of interests are Data Mining, Programming Languages, Software Engineering, Databases etc. Starting IT career in .
Publicado por LAP LAMBERT Academic Publishing Nov 2016, 2016
ISBN 10: 365997921X ISBN 13: 9783659979217
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Newer intrusions are coming out every day with the all-way growth of the Internet. In this context, this book proposes a hybrid approach of intrusion detection along with architecture. The proposed architecture is flexible enough to carry intrusion detection tasks either by using a single module or by using multiple modules. Two modules - (1) Clustering-Outlier detection followed by SVM classification and (2) Incremental SVM with Half-partition method, are proposed in the book. Firstly, this work develops the 'Clustering-Outlier Detection' algorithm that combines k-Medoids clustering and Outlier analysis. Secondly, this book introduces the Half-partition strategy and also designs 'Candidate Support Vector Selection' algorithm for incremental SVM. This book is intended for the people who are working in the field of Intrusion Detection and Data Mining. Researchers and Scholars who are interested in k-Means and k-Medoids clustering and SVM classification in particular, will find this book useful. Students who want to pursue their research work in the fields of Information Security and Data Mining may also consider this as a good reference. 140 pp. Englisch.
Publicado por LAP LAMBERT Academic Publishing, 2016
ISBN 10: 365997921X ISBN 13: 9783659979217
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 55,90
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Newer intrusions are coming out every day with the all-way growth of the Internet. In this context, this book proposes a hybrid approach of intrusion detection along with architecture. The proposed architecture is flexible enough to carry intrusion detection tasks either by using a single module or by using multiple modules. Two modules - (1) Clustering-Outlier detection followed by SVM classification and (2) Incremental SVM with Half-partition method, are proposed in the book. Firstly, this work develops the 'Clustering-Outlier Detection' algorithm that combines k-Medoids clustering and Outlier analysis. Secondly, this book introduces the Half-partition strategy and also designs 'Candidate Support Vector Selection' algorithm for incremental SVM. This book is intended for the people who are working in the field of Intrusion Detection and Data Mining. Researchers and Scholars who are interested in k-Means and k-Medoids clustering and SVM classification in particular, will find this book useful. Students who want to pursue their research work in the fields of Information Security and Data Mining may also consider this as a good reference.
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Añadir al carritoHRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Añadir al carritoHardcover. Condición: Brand New. 260 pages. 9.69x6.88x0.69 inches. In Stock. This item is printed on demand.
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Añadir al carritoHRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: moluna, Greven, Alemania
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dan Dobrota is a Professor at Lucian Blaga University of Sibiu, Romania. He obtained his undergraduate degree in Machine Building Technology (1994) from University of Craiova, Romania. He received his Ph.D. in Technology of Materials field from th.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoBuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The proceedings publish selected papers from the 2nd International Conference on New Computational Social Science, focusing on the following five aspects: Big data acquisition and analysis, Integration of qualitative research and quantitative research, Sociological Internet experiment research, Application of ABM simulation method in Sociology Research, Research and development of new social computing tools.With the rapid development of information technology, especially sweeping progress in the Internet of things, cloud computing, social networks, social media and big data, social computing, as a data-intensive science, is an emerging field that leverages the capacity to collect and analyze data with an unprecedented breadth, depth and scale. It represents a new computing paradigm and an interdisciplinary field of research and application. A broad comprehension of major topics involved in social computing is important for both scholars and practitioners. This proceedings presents and discusses key concepts and analyzes the state-of-the-art of the field. The conference not only gave insights on social computing, but also affords conduit for future research in the field. Social computing has two distinct trends: One is on the social science issues, such as computational social science, computational sociology, social network analysis, etc; the other is on the use of computational techniques. Finally, some new challenges ahead are summarized, including interdisciplinary cooperation and training, big data sharing for scientific data mashups, and privacy protect.